Abstract
Noncommunicable diseases (NCD) are the leading causes of death and the main public health problem worldwide [1] and are associated with an acute picture of dyslipidemia that is part of the main risk factors along with smoking, sedentary activities, incorrect diet, and genetic factors that have caused diseases such as metabolic syndrome, oncological, cardiology, neurological and respiratory diseases. NCD are a major problem in low-income and middle-income countries, consuming increasing proportions of health care budgets. NCD are among the leading causes of disability and ill health and are the leading cause of preventable and premature death, having a significant impact on economies. NCD generate large out-of-pocket health costs for both individuals and families, as well as huge health outlays in national budgets. The analysis proposed can provide critical information to monitor trends in population health outcomes, recognize the pattern of diseases and injuries affecting premature mortality and disability. This paper shows an approach for the identification of the behavior of four main NCD (cardiovascular diseases, respiratory diseases, diabetes mellitus, and neoplasms) along thirteen countries selected and various economic variables related to the health and work issues from 1961 to 2021 with unbalanced data. The primary focus is the analysis on mortality in population within working age.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Cordova-Villalobos, J.A., et al.: Chronic noncommunicable diseases in Mexico: epidemiological overview and comprehensive prevention. Salud Pública de México 50(5), 419–427 (2008). https://doi.org/10.1590/s0036-36342008000500015
WHO, World Health Organization: The top 10 causes of death (2020). https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-deat
OPS, Pan American Health Organization: Leading causes of mortality and disability (2022). Last accessed 2023/29/03. https://www.paho.org/es/enlace/causas-principales-mortalidad-discapacidad
Jaspers, L., et al.: The global impact of non-communicable diseases on households and impoverishment: a systematic review. Eur. J. Epidemiol. 30(3), 163–188 (2014). https://doi.org/10.1007/s10654-014-9983-3
Chaker, L., et al.: The global impact of non-communicable diseases on macro-economic productivity: a systematic review. Eur. J. Epidemiol. 30(5), 357–395 (2015). https://doi.org/10.1007/s10654-015-0026-5
Rodríguez-Aguilar, R., Rivera-Peña, G., Ramírez-Pérez, H.X.: Household expenditure in health in Mexico, 2016. In: Vasant, P., Zelinka, I., Weber, G.-W. (eds.) ICO 2019. AISC, vol. 1072, pp. 662–670. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-33585-4_64
Rashida, M., Iffath, F., Karim, R., Arefin, M.S.: Trends and techniques of biomedical text mining: a review. In: Vasant, P., Zelinka, I., Weber, G.-W. (eds.) ICO 2021. LNNS, vol. 371, pp. 968–980. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-93247-3_92
Wang, Y., Wang, J.: Modelling and prediction of global non-communicable diseases. BMC Public Health 20, 1–13 (2020). https://doi.org/10.1186/s12889-020-08890-4
Allen, L.N., Wigley, S., Holmer, H.: Implementation of non-communicable disease policies from 2015 to 2020: a geopolitical analysis of 194 countries. Lancet Glob. Health 9(11), e1528–e1538 (2021). https://doi.org/10.1016/S2214-109X(21)00359-4
Perazzi, J.R., Merli, G.O.: Panel data regression models and their application in the evaluation of impacts of social programs. Telos 16(1), 157–164 (2014). https://www.redalyc.org/pdf/993/99330402007.pdf
IHME—Institute for Health Metrics and Evaluation: Global Burden of Disease Study 2019, Results (2020). https://vizhub.healthdata.org/gbd-results/
WHO, World Health Organization: The Global Health Observatory (2022). Last accessed 2023/03/29. https://www.who.int/data/gho/data/indicators/indicator-details/GHO/mean-bmi-(kg-m-)-(age-standardized-estimate
OECD: Working Age Population (Indicator) (2022). https://doi.org/10.1787/d339918b-en. https://data.oecd.org/pop/working-age-population.htm
FAO: Food Balances (2022). Last accessed 2023/03/29. https://www.fao.org/faostat/en/#data/FBSH
Wooldridge, J.M.: Introductory econometrics: a modern approach. Cengage Learning (2015)
de la Torre Díez, I., Garcia-Zapirain, B., Méndez-Zorrilla, A., López-Coronado, M.: Monitoring and follow-up of chronic heart failure: a literature review of eHealth applications and systems. J. Med. Syst. 40(7), 1–9 (2016). https://doi.org/10.1007/s10916-016-0537-y
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Domínguez-Miranda, S.A., Rodriguez-Aguilar, R. (2023). The Economic Dimensions of the Non-communicable Diseases: A Panel Data Study. In: Vasant, P., et al. Intelligent Computing and Optimization. ICO 2023. Lecture Notes in Networks and Systems, vol 855. Springer, Cham. https://doi.org/10.1007/978-3-031-50158-6_14
Download citation
DOI: https://doi.org/10.1007/978-3-031-50158-6_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-50157-9
Online ISBN: 978-3-031-50158-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)